



'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_									=    logging.get_logger(__name__)

lowercase_									=    {
    "edbeeching/decision-transformer-gym-hopper-medium": (
        "https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}






class __A     (    A		):



 '''simple docstring'''







 __lowerCamelCase       :			List[Any]		=			'decision_transformer'
 __lowerCamelCase       :			Dict		=			['past_key_values']
 __lowerCamelCase       :			str		=			{
     'max_position_embeddings': 'n_positions',
     'num_attention_heads': 'n_head',
     'num_hidden_layers': 'n_layer',
 }



 def __init__(self					,  A=17					,  A=4					,  A=128					,  A=4_096					,  A=True					,  A=1					,  A=1_024					,  A=3					,  A=1					,  A=None					,  A="relu"					,  A=0.1					,  A=0.1					,  A=0.1					,  A=1E-5					,  A=0.02					,  A=True					,  A=True					,  A=50_256					,  A=50_256					,  A=False					,  A=False					,  **A					,  )       ->	Union[str, Any]:


      """simple docstring"""



      _a           =    state_dim
      _a           =    act_dim
      _a           =    hidden_size
      _a           =    max_ep_len
      _a           =    action_tanh
      _a           =    vocab_size
      _a           =    n_positions
      _a           =    n_layer
      _a           =    n_head
      _a           =    n_inner
      _a           =    activation_function
      _a           =    resid_pdrop
      _a           =    embd_pdrop
      _a           =    attn_pdrop
      _a           =    layer_norm_epsilon
      _a           =    initializer_range
      _a           =    scale_attn_weights
      _a           =    use_cache
      _a           =    scale_attn_by_inverse_layer_idx
      _a           =    reorder_and_upcast_attn

      _a           =    bos_token_id
      _a           =    eos_token_id

      super().__init__(bos_token_id=A					,  eos_token_id=A					,  **A			)







'''simple docstring'''


def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				print("""\nThe shortest path matrix using Floyd Warshall algorithm\n"""	)
				for i in range(SCREAMING_SNAKE_CASE__	):
								for j in range(SCREAMING_SNAKE_CASE__	):
												if dist[i][j] != float("""inf"""	):
																print(int(dist[i][j]	)				, end="""\t"""	)
												else:
																print("""INF"""				, end="""\t"""	)
								print()







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Any							= [[float("""inf"""	) for _ in range(SCREAMING_SNAKE_CASE__	)] for _ in range(SCREAMING_SNAKE_CASE__	)]

				for i in range(SCREAMING_SNAKE_CASE__	):
								for j in range(SCREAMING_SNAKE_CASE__	):
												_SCREAMING_SNAKE_CASE					:			List[str]							= graph[i][j]

												# check vertex k against all other vertices (i, j)
				for k in range(SCREAMING_SNAKE_CASE__	):
								# looping through rows of graph array
								for i in range(SCREAMING_SNAKE_CASE__	):
												# looping through columns of graph array
												for j in range(SCREAMING_SNAKE_CASE__	):
																if (
																    dist[i][k] != float("""inf"""	)
																    and dist[k][j] != float("""inf"""	)
																    and dist[i][k] + dist[k][j] < dist[i][j]
																):
																				_SCREAMING_SNAKE_CASE					:			int							= dist[i][k] + dist[k][j]

				_print_dist(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)
				return dist, v


if __name__ == "__main__":
				UpperCAmelCase_						:  str				  =						int(input('Enter number of vertices: '))
				UpperCAmelCase_						:  Union[str, Any]				  =						int(input('Enter number of edges: '))

				UpperCAmelCase_						:  Dict				  =						[[float('inf') for i in range(v)] for j in range(v)]

				for i in range(v):
								UpperCAmelCase_						:  Union[str, Any]				  =						0.0

								# src and dst are indices that must be within the array size graph[e][v]
								# failure to follow this will result in an error
				for i in range(e):
								print('\nEdge ', i + 1)
								UpperCAmelCase_						:  int				  =						int(input('Enter source:'))
								UpperCAmelCase_						:  List[str]				  =						int(input('Enter destination:'))
								UpperCAmelCase_						:  List[str]				  =						float(input('Enter weight:'))
								UpperCAmelCase_						:  int				  =						weight

				floyd_warshall(graph, v)

				# Example Input
				# Enter number of vertices: 3
				# Enter number of edges: 2

				# # generated graph from vertex and edge inputs
				# [[inf, inf, inf], [inf, inf, inf], [inf, inf, inf]]
				# [[0.0, inf, inf], [inf, 0.0, inf], [inf, inf, 0.0]]

				# specify source, destination and weight for edge #1
				# Edge  1
				# Enter source:1
				# Enter destination:2
				# Enter weight:2

				# specify source, destination and weight for edge #2
				# Edge  2
				# Enter source:2
				# Enter destination:1
				# Enter weight:1

				# # Expected Output from the vertice, edge and src, dst, weight inputs!!
				# 0		INF	INF
				# INF	0	2
				# INF	1	0




